To identify and explore the communities of topic \(\#88\) , we employ the (weighted) walk-trap method proposed by [1]}For this purpose we have employed igraph's weighted walktrap community algorithm implementation, using 4-steps random walks based on LDA2Net-weights.. By so doing, we obtained a set of topic communities each of which can be represented as a network. In Figure REF , the top 50 bigrams (by LDA2Net-weight) of the four largest communities (i.e. subtopics) of topic \(\#88\)  are represented using a hierarchical network layout.
The first community by size (Figure REF  (a) ) focuses on chemical compounds and antiviral drug design. The second community (Figure REF  (b) ) is about Mpro inhibitors and binding mechanisms. The third community (Figure REF  (c) ) captures some methodological aspects of topic \(\#88\)  and focuses on health professionals (e.g., MD and MA), study types (e.g., vivo\(\rightarrow \) experiments and pharmacokinetic\(\rightarrow \) studies), result-related explanations (e.g., results\(\rightarrow \) indicate and approach\(\rightarrow \) demonstrated). Finally, the fourth community (Figure REF  (d) ) is about viral RNA replication and transcription.
